Image metadata is well-known, and is useful in retrieving desired images from a large collection of images. The Kodak DC265™ camera formulates many metadata items, such as the date/time, camera lens setting, scene light level, etc. when the picture is taken, and stores this metadata within the Exif/JPEG digital image file. Unfortunately, this metadata cannot identify the subject of the photo, or whether this particular photo is one of the user's “favorite” photos. It is this latter type of information that is most useful in quickly and easily retrieving desired images from a large collection of pictures.
Many software applications allow the user to manually type in text, such as a “picture title” or “picture description,” and store this text within the image file. This could be used to add a description including the people, events, or type of photo. The text strings from all images in the database could later be searched to retrieve images having the names, events, etc. of interest. Unfortunately, this is an extremely tedious method of adding metadata. In addition, since the user may type in different text to describe the same item (e.g. Matt, Matthew, or X-mas, Christmas) the database may not contain consistent names for the same picture categories. Some particular software applications, such as Image Expert 2000™ developed by Sierra Imaging Inc., allow the user to add keywords to captured images. The keywords are categorized as “location,” “occasion,” “photographer,” and “subject.” While viewing a group of thumbnail images, a user can create keywords in these categories and assign the keywords to one or more captured images by selecting the thumbnails and keywords. The keywords from all images in the database can later be searched to retrieve images that were assigned to those particular keywords.
Unfortunately, these conventional software applications make it difficult for an untrained consumer to categorize their images in a way that enables them to later locate their favorite images of a selected subject. What is needed is a simple, fast method for the user to add emotional or aesthetic based type metadata to a collection of images, and to use this emotional or aesthetic based metadata to retrieve images of interest.